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[所需支持/长期护理认证风险评估量表的开发:一项使用基洪检查表和医学评估数据的纵向研究]

[Development of risk assessment scales for Needed Support/Long-Term Care certification: A longitudinal study using the Kihon Checklist and medical assessment data].

作者信息

Tsuji Taishi, Takagi Daisuke, Kondo Naoki, Kondo Katsunori

机构信息

Center for Preventive Medical Sciences, Chiba University.

Department of Health and Social Behavior, School of Public Health, The University of Tokyo.

出版信息

Nihon Koshu Eisei Zasshi. 2017;64(5):246-257. doi: 10.11236/jph.64.5_246.

DOI:10.11236/jph.64.5_246
PMID:28626152
Abstract

Objectives This study aimed to develop risk assessment scales for predicting the incidence of Needed Support/Long-Term Care certification, by aggregating data from the Kihon Checklist, medical assessments, and long-term care insurance certification during a follow-up period (a maximum of 4 years and 2 months) conducted in a municipality.Methods This retrospective cohort study included 72,127 older adults aged 65 years or older living in K City (an ordinance-designated city) who responded to the Kihon Checklist in 2011. We linked their medical assessment data (examined/unexamined, blood pressure, and five blood biochemical items) from 2011 and information on the incidence of long-term care insurance certification from 2011 to 2015 to the Kihon Checklist data (the 12 essential items and seven optional items from the Needs Survey). We constructed four Cox proportional hazards models as follows: 1) age, sex, and the Needs Survey's 12 essential items; 2) model 1 plus seven optional items; 3) model 2 plus examined/unexamined at medical assessment; and 4) model 3 plus blood pressure and five blood biochemical items, as independent variables. Recent requirement for Support/Long-Term Care certification was included as an outcome with stepwise forward selection. We assigned scores for each item based on the non-standardized regression coefficients obtained (B) and the sum of those scores was used to establish the risk assessment scales for predicting Needed Support/Long-Term Care certification from each model. A receiver operating characteristic (ROC) analysis was conducted to estimate the sensitivity and specificity in order to compare predictive validity of the scales.Results During the follow-up period, 11,039 (15.3%) individuals required a new incidence of a Needed Support/Needed Long-Term Care certification. A risk assessment scale of 0-55 was established based on age, sex, and the 10 essential items from the Needs Survey's. The incidence of certification were 3.2%, 14.7%, 31.6%, 56.7%, and 75.0% at scores of 10, 20, 30, 40, and 50, respectively. The area under the ROC curve (AUC) was 0.783, and the sensitivity and the specificity were 0.705 and 0.731, respectively (cut-off: 21/22). These values remained almost unchanged despite the addition of optional and medical assessment items (AUC: 0.786-0.787, sensitivity: 0.721-0.730, and specificity: 0.710-0.717).Conclusion Although the medical assessment data was not aggregated, the scale developed from the Kihon Checklist's 10 items (included in the Needs Survey's essential items) is useful for predicting the incidence of Needed Support/Long-Term Care certification. The scale, which evaluates the risk of needed support/long-term care at individual and community levels, was developed using the existing Kihon Checklist data or the Needs Survey's data collected subsequently by municipalities.

摘要

目的 本研究旨在通过汇总在一个市政辖区进行的随访期(最长4年零2个月)内来自基準检查表、医学评估和长期护理保险认证的数据,制定用于预测所需支持/长期护理认证发生率的风险评估量表。

方法 这项回顾性队列研究纳入了2011年对基準检查表做出回应的、居住在K市(政令指定城市)的72127名65岁及以上的老年人。我们将他们2011年的医学评估数据(检查/未检查、血压和五项血液生化指标)以及2011年至2015年的长期护理保险认证发生率信息与基準检查表数据(需求调查中的12项基本项目和7项可选项目)相链接。我们构建了四个Cox比例风险模型如下:1)年龄、性别和需求调查的12项基本项目;2)模型1加上7项可选项目;3)模型2加上医学评估时的检查/未检查情况;4)模型3加上血压和五项血液生化指标,作为自变量。将近期所需支持/长期护理认证作为结果,采用逐步向前选择法。我们根据获得的非标准化回归系数(B)为每个项目赋值,这些分数的总和用于建立每个模型预测所需支持/长期护理认证的风险评估量表。进行了受试者工作特征(ROC)分析以估计敏感性和特异性,以便比较量表的预测效度。

结果 在随访期内,11039人(15.3%)需要新的所需支持/所需长期护理认证发生率。基于年龄、性别和需求调查中的10项基本项目建立了0至55的风险评估量表。分数为10、20、30、40和50时,认证发生率分别为3.2%、14.7%、31.6%、56.7%和75.0%。ROC曲线下面积(AUC)为0.783,敏感性和特异性分别为0.705和0.731(临界值:21/22)。尽管添加了可选项目和医学评估项目,这些值几乎保持不变(AUC:0.786 - 0.787,敏感性:0.721 - 0.730,特异性:0.710 - 0.717)。

结论 尽管未汇总医学评估数据,但从基準检查表的10项(包含在需求调查的基本项目中)开发的量表对于预测所需支持/长期护理认证的发生率是有用的。该量表在个体和社区层面评估所需支持/长期护理的风险,是使用现有的基準检查表数据或市政当局随后收集的需求调查数据开发的。

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